|
on South East Asia |
| By: | Teuku Riefky (Institute for Economic and Social Research, Faculty of Economics and Business, Universitas Indonesia (LPEM FEB UI)); Faizal Rahmanto Moeis (Institute for Economic and Social Research, Faculty of Economics and Business, Universitas Indonesia (LPEM FEB UI)); Yusuf Sofiyandi (Institute for Economic and Social Research, Faculty of Economics and Business, Universitas Indonesia (LPEM FEB UI)); Muhammad Adriansyah (Institute for Economic and Social Research, Faculty of Economics and Business, Universitas Indonesia (LPEM FEB UI)); Anas Izzuddin (Institute for Economic and Social Research, Faculty of Economics and Business, Universitas Indonesia (LPEM FEB UI)); Aqilah Farhani (Institute for Economic and Social Research, Faculty of Economics and Business, Universitas Indonesia (LPEM FEB UI)); Sendy Jasmine (Institute for Economic and Social Research, Faculty of Economics and Business, Universitas Indonesia (LPEM FEB UI)) |
| Abstract: | Indonesia is in the middle of its long-term development challenge to escape the ‘middle-income trap’. As often as developing countries face the same challenge, one common strategy to be implemented by the Government of Indonesia (GoI) is to develop a massive infrastructure plan across the country. Despite the ambitious development and planning of infrastructure in Indonesia, Indonesia’s current state of infrastructure is under threat due to natural disasters. Natural disasters cause damage to infrastructure, which affects the infrastructure’s ability to provide benefits for the society and economy. The geographical position of Indonesia and climate-related factors have raised the exposure of environmental risks and climate change to Indonesia’s infrastructure. In general, the current infrastructure conditions in Indonesia are simply not resilient enough to endure future disaster and climate change risks. Therefore, to mitigate and adapt to these risks, Indonesia should build resilient infrastructures, which are able to withstand damage or disruptions, but if affected, can be readily and cost-effectively restored (Scalingi, 2007). Indonesia has created several national-level development plans for resilient infrastructure development, such as the 2014 RAN-API, 2012 RAN-MAPI, and the 2020–2024 RPJMN that complement each other, emphasize resilient infrastructure to reduce losses due to disasters. Regionally, several districts have their own climate change adaption disaster risk reduction plan, such as Makassar City and Kupang City, that accommodate local disaster and climate risks. However, not all districts have designed their climate change adaptation disaster risk reduction plan as it is not mandatory. Moreover, the GoI has created several regulations regarding resilient infrastructure, such as Green Buildings, infrastructure in tsunami-prone areas, and building technical requirements. These plans and regulations have also been supported by several actors, both from the public and private sector. |
| Keywords: | climate change — development planning — Indonesia — natural disasters — resilient infrastructure |
| JEL: | H54 O21 Q54 Q58 R58 |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:lpe:wpaper:202164&r= |
| By: | Liebenehm, Sabine; Menkhoff, Lukas; Waibel, Hermann |
| Keywords: | Risk and Uncertainty |
| Date: | 2021–08 |
| URL: | http://d.repec.org/n?u=RePEc:ags:iaae21:314997&r= |
| By: | Kohnert, Dirk |
| Abstract: | The ASEAN summit of October 2021 showed the increased geopolitical importance of the Indo-Pacific realm. Today ASEAN is the most successful regional organization in Asia and the second largest worldwide behind the EU. The establishment of the New Asian-African Strategic Partnership (NAASP) more than 15 years before (2005) aimed to revive the Bandung spirit of the non-aligned movement of 1955. This time with a stronger focus on economic ties. In 2013 these countries counted around 620 million inhabitants or 8.8% of the world population. They wanted to fight colonialism and neocolonialism by promoting Afro-Asiatic economic and cultural cooperation. Almost all member countries gained sovereignty and political independence by the 1960s and 1970s, except for Palestine. However, the aftermath of the Bandung conference also promoted negative developments, including the polarization of Asian countries, the strengthening of political authoritarianism, and regional interventions. In addition, most countries continued to grapple with economic and political challenges, including poverty, debt burdens, backwardness, ignorance, disease, and environmental degradation. Their access to the markets of the industrialized countries also remained limited. At the global level, the NAASP received little attention so far. Despite the longstanding rhetoric of Asia-Africa solidarity, Asia and Africa still lack formal institutional and trade links. Although interregional trade increased, Africa remained a small part of ASEAN with only around 2% of its total market. The most important trading countries of ASEAN with Africa were Thailand, Indonesia, and Singapore, while South Africa, Nigeria, and Egypt were the largest African import markets. |
| Keywords: | ASEAN, NAASP, Asia, Africa, economic growth, international trade, free trade area, customs union, Non-Aligned Movement, Indonesia, South Africa, Thailand, Singapore, Nigeria, Egypt |
| JEL: | F13 F15 F36 F54 N15 N17 O17 O19 O53 O55 Z13 |
| Date: | 2021–11–16 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:110709&r= |
| By: | Kohnert, Dirk |
| Abstract: | ABSTRACT & RÉSUMÉ : ASEAN – African relations. Towards a new partnership ? ----- The ASEAN summit of October 2021 showed the increased geopolitical importance of the Indo-Pacific realm. Today ASEAN is the most successful regional organization in Asia and the second largest worldwide behind the EU. The establishment of the New Asian-African Strategic Partnership (NAASP) more than 15 years before (2005) aimed to revive the Bandung spirit of the non-aligned movement of 1955. This time with a stronger focus on economic ties. In 2013 these countries counted around 620 million inhabitants or 8.8% of the world population. They wanted to fight colonialism and neocolonialism by promoting Afro-Asiatic economic and cultural cooperation. Almost all member countries gained sovereignty and political independence by the 1960s and 1970s, except for Palestine. However, the aftermath of the Bandung conference also promoted negative developments, including the polarization of Asian countries, the strengthening of political authoritarianism, and regional interventions. In addition, most countries continued to grapple with economic and political challenges, including poverty, debt burdens, backwardness, ignorance, disease, and environmental degradation. Their access to the markets of the industrialized countries also remained limited. At the global level, the NAASP received little attention so far. Despite the longstanding rhetoric of Asia-Africa solidarity, Asia and Africa still lack formal institutional and trade links. Although interregional trade increased, Africa remained a small part of ASEAN with only around 2% of its total market. The most important trading countries of ASEAN with Africa were Thailand, Indonesia, and Singapore, while South Africa, Nigeria, and Egypt were the largest African import markets. RÉSUMÉ : : Le sommet de l'ASEAN d'octobre 2021 a montré l'importance géopolitique accrue de la region indo-pacifique. Aujourd'hui, l'ANASE est l'organisation régionale la plus performante d'Asie et la deuxième au monde derrière l'UE. La création du Nouveau partenariat stratégique Asie-Afrique (NAASP) plus de 15 ans auparavant (2005) visait à raviver l'esprit de Bandung du mouvement des non-alignés de 1955. Cette fois en mettant davantage l'accent sur les liens économiques. En 2013, ces pays comptaient environ 620 millions d'habitants soit 8,8% de la population mondiale. Ils voulaient combattre le colonialisme et le néocolonialisme en promouvant la coopération économique et culturelle afro-asiatique. Presque tous les pays membres ont acquis leur souveraineté et leur indépendance politique dans les années 1960 et 1970, à l'exception de la Palestine. Cependant, les conséquences de la conférence de Bandung ont également favorisé des développements négatifs, notamment la polarisation des pays asiatiques, le renforcement de l'autoritarisme politique et les interventions régionales. En outre, la plupart des pays ont continué à faire face à des défis économiques et politiques, notamment la pauvreté, le fardeau de la dette, le retard, l'ignorance, la maladie et la dégradation de l'environnement. Leur accès aux marchés des pays industrialisés restait également limité. Au niveau mondial, le NAASP a reçu peu d'attention jusqu'à présent. Malgré la rhétorique de longue date de la solidarité Asie-Afrique, l'Asie et l'Afrique manquent encore de liens institutionnels et commerciaux formels. Bien que le commerce interrégional ait augmenté, l'Afrique est restée une petite partie de l'ASEAN avec seulement environ 2% de son marché total. Les principaux pays commerçants de l'ASEAN avec l'Afrique étaient la Thaïlande, l'Indonésie et Singapour, tandis que l'Afrique du Sud, le Nigéria et l'Égypte étaient les plus grands marchés d'importation africains. |
| Keywords: | ANASE, ASEAN, NAASP, Asie du Sud-Est, Afrique, croissance économique, commerce international, zone de libre échange, union douanière, mouvement des non-alignés, Indonésie, Afrique du Sud, Thaïlande, Singapour, Nigeria, Égypte |
| JEL: | F13 F15 F36 F54 N15 N17 O17 O19 O53 O55 Z13 |
| Date: | 2021–11–16 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:110710&r= |
| By: | Valera, Harold Glenn; Yamano, Takashi; Pede, Valerien |
| Keywords: | International Relations/Trade, Agricultural and Food Policy |
| Date: | 2021–08 |
| URL: | http://d.repec.org/n?u=RePEc:ags:iaae21:315265&r= |
| By: | Le, Duong Trung (World Bank); Pham, Thanh Minh (Binghamton University, New York); Polachek, Solomon (Binghamton University, New York) |
| Abstract: | This paper examines the long-term health impact of Agent Orange, a toxic military herbicide containing dioxin that was used extensively during the U.S.-Vietnam war in the 1960-70s. Using a nationally representative health survey and an instrumental variable approach that addresses the potential endogeneity in the location and the intensity of U.S. defoliant missions, we report several findings. First, relative to the average prevalence rate of the sample population, we find that Vietnamese civilians located in a commune one-standard-deviation more exposed to herbicide during the war were 19.75 percent more likely to suffer from a health disease medically linked to Agent Orange three decades later. Second, disaggregating by disease types, we observe significant effects on blood pressure disease and mobility disability. Third, across cohorts, we find significant detrimental impact on those born before herbicide missions ended, especially among wartime children, infants, and those in-utero during the 1962-1971 period. |
| Keywords: | Agent Orange, herbicide, health, conflicts, Vietnam war |
| JEL: | N45 I10 Q53 |
| Date: | 2021–10 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp14782&r= |
| By: | International Monetary Fund |
| Abstract: | The A remote technical assistance (TA) mission to the Ministry of Economy and Finance (MEF) was conducted during ten days over the period of August 31–November 30, 2020.1 This activity was part of Cambodia’s participation in the Japan-funded Government Finance Statistics (GFS) and Public Sector Debt Statistics (PSDS) Project for selected Asian countries (JSA3)2. The overall goal of the JSA3 Project is to assist the MEF in strengthening compilation and dissemination of fiscal data in line with the GFS Manual 2014 and the PSDS: Guide for Compilers and Users to support macro-fiscal surveillance and decision making. The mission liaised with Mr. Alexandros Mourmouras, Director of the Capacity Development Office in Thailand (CDOT), Mr. Rifaat Basanti, the IMF Regional JSA3 GFS/PSDS Project Manager, Mr. Suhas Joshi, the IMF Regional Treasury Advisor—both in the CDOT, Mr. Yasuhisa Ojima, the IMF’s Resident Representative for Cambodia, and Ms. Magdalena Tomczynska-Smith, the IMF’s Budget Planning Advisor for Cambodia. The mission would like to thank the authorities for their excellent collaboration and support (Appendix I lists the main official contacts). |
| Keywords: | PSDS compilation; government finance statistics yearbook; IMF's Statistics Department; GFS classification; IMF activity; Government finance statistics; Financial statements; PFM information systems; Fiscal accounting and reporting |
| Date: | 2021–10–20 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfscr:2021/233&r= |
| By: | Nakamura, Nobuyuki; Suzuki, Aya |
| Keywords: | Health Economics and Policy, Labor and Human Capital |
| Date: | 2021–08 |
| URL: | http://d.repec.org/n?u=RePEc:ags:iaae21:314965&r= |
| By: | International Monetary Fund |
| Abstract: | This technical assistance (TA) report on government finance statistics (GFS) covers the remote TA to the Ministry of Finance (MOF) during September 21–October 2 and December 14–18, 2020 and March 9–13 and April 19–23, 2021 (which was extended to May 2021). These peripatetic activities were conducted remotely due to the travel restrictions resulting from the COVID-19 situation. This report documents the main achievements from these activities. These activities were part of the GFS and Public Sector Debt Statistics (PSDS) project funded by the Government of Japan (JSA3) and implemented by the IMF Statistics Department (STA) and the IMF Capacity Development Office in Thailand (CDOT). |
| Keywords: | MOF website; IMF capacity development office; IMF's Statistics Department; MOF staff; government finance information system; TA for April; Government finance statistics; COVID-19; Budget planning and preparation; Data collection; Budget execution and treasury management |
| Date: | 2021–11–01 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfscr:2021/239&r= |
| By: | Scott, Douglas (University of Oxford); Freund, Richard (University of Oxford); Favara, Marta (University of Oxford); Porter, Catherine (Lancaster University); Sanchez, Alan (Group for the Analysis od Development (GRADE)) |
| Abstract: | This paper analyses the difference in short-term employment recovery between young men and women in India, Peru and Vietnam following the national lockdowns imposed in all three countries during 2020. We employ a mediation model to establish whether - and to what extent – commonly suggested mechanisms are responsible for a relatively slower recovery among young women and an increase in the gender employment gap. In line with the literature, we find evidence that the unequal distribution of caring responsibilities explains a meaningful proportion of the disparity in Peru and Vietnam, but a smaller share of the change in the employment gap in India. Contrary to the previous literature, however, we find little evidence that the work activity performed before the pandemic explains the slower female recovery in any of the three study countries. |
| Keywords: | COVID-19, job loss, work resilience, gender gap |
| JEL: | J21 J16 J6 |
| Date: | 2021–11 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp14829&r= |
| By: | International Monetary Fund |
| Abstract: | A remote follow-up technical assistance (TA) mission on government finance statistics (GFS) and public sector debt statistics (PSDS) was conducted, with the assistance of the Department of Finance (DOF), during October 19–27, 2020. The mission made further progress in implementing recommendations of previous TA missions in the area of GFS and PSDS. The mission was undertaken within the GFS/PSDS TA project for Asia, funded by the Government of Japan (JSA3). |
| Keywords: | Government finance statistics yearbook; General Government GFS data; GFI debt; data SGGO; authorities of the Philippines; staff team of the International Monetary Fund; Government finance statistics; Domestic debt; Exchange rates; Asia and Pacific; Global |
| Date: | 2021–10–20 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfscr:2021/232&r= |
| By: | Bhumjai Tangsawasdirat; Suranan Tanpoonkiat; Burasakorn Tangsatchanan |
| Abstract: | This paper aims to provide an introduction to Credit Risk Database (CRD), a collection of financial and non-financial data for SME credit risk analysis, for Thailand. Aligning with the Bank of Thailand (BOT)’s strategic plan to develop the data ecosystem to help reduce asymmetric information problem in the financial sector, CRD is an initiative to effectively utilize data already collected from financial institutions as a part of the BOT’s supervisory mandate. Our first use case is intended to help improve financial access for SMEs, by building credit risk models that can work as a complementary tool to help financial institutions and Credit Guarantee Corporation assess SMEs financial prospects in parallel with internal credit score. Focusing on SMEs who are new borrowers, we use only SME’s financial and non-financial data as our explanatory variables while disregarding past default-related data such as loan repayment behavior. Credit risk models of various methodologies are then built from CRD data to allow financial institutions to conduct effective risk-based pricing, offering different sets of interest rates and loan terms. Statistical methods (i.e. logit regression and credit scoring) and machine learning methods (i.e. decision tree and random forest) are used to build credit risk models that can help quantify the SME’s one-year forward probability of default. Out-of-sample prediction results indicate that the statistical and machine learning models yield reasonably accurate probability of default predictions, with the maximum Area under the ROC Curve (AUC) at approximately 70-80%. The model with the best performance, as compared by the maximum AUC, is the random forest model. However, the credit scoring model that is developed from logistic regression of weighted-of-evidence variables is more user-friendly for credit loan providers to interpret and develop practical application, achieving the second-best AUC. |
| Keywords: | Credit Risk Database; Credit Score; Credit Risk Assessment; Credit Scoring Model; Thai SMEs |
| JEL: | C52 C53 C55 D81 G21 G32 |
| Date: | 2021–11 |
| URL: | http://d.repec.org/n?u=RePEc:pui:dpaper:168&r= |
| By: | International Monetary Fund |
| Abstract: | With the support of the IMF’s Asia and Pacific Department (APD) and the Bangko Sentral ng Pilipinas (BSP), an IMF Statistics Department (STA)’s remote financial soundness indicators (FSIs) technical assistance (TA) mission took place during April 30–May 14, 2021. The main objective of the mission was to assist the BSP in compiling FSI for the other financial corporations (OFCs) sector, in line with the 2019 Financial Soundness Indicators Compilation Guide (Guide). Specifically, the Guide recommends compiling indicators for money market funds, insurance corporations, and pension funds, as well as for the total OFC sector. The work of the mission was facilitated by the excellent collaboration of BSP’s staff, in particular of the Department of Economic Statistics (DES). The list of officials met during the mission can be found in Appendix I. |
| Date: | 2021–11–17 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfscr:2021/247&r= |
| By: | Rogelio Mercado Jr. (South East Asian Central Banks (SEACEN) Research and Training Centre); Shanty Noviantie (South East Asian Central Banks (SEACEN) Research and Training Centre) |
| Abstract: | This paper uses a dataset on bilateral capital flows to construct a financial centrality measure for 64 advanced and emerging economies from 2000-16 to capture an economy’s importance within the global financial flows network. The results highlight the varying significance of network systemic and idiosyncratic factors in explaining financial centrality across different types of investments and residency of investors. Most notably, the findings show that financial centres have deeper and more developed financial system, implying their importance in global financial intermediation. |
| Keywords: | financial centrality, financial depth, network analysis |
| JEL: | D85 F21 F36 G15 |
| Date: | 2019–12 |
| URL: | http://d.repec.org/n?u=RePEc:tcd:tcduee:tep1119&r= |
| By: | Deni Irawan (Institute for Economic and Social Research, Faculty of Economics and Business, Universitas Indonesia (LPEM FEB UI); Crawford School of Public Policy, Australian National University, Australia; Research Institute of Economy, Trade and Industry (RIETI), Japan); Tatsuyoshi Okimoto (Crawford School of Public Policy, Australian National University, Australia; Research Institute of Economy, Trade and Industry (RIETI), Japan; Centre for Applied Macroeconomic Analysis (CAMA), Australian National University, Australia) |
| Abstract: | This study examines the conditional capital surplus and shortfall dynamics of renewable and non-renewable resource firms. To this end, this study uses the systemic risk index by Brownlees & Engle (2017) and considers two conditional systemic events, namely, the stock market crash and the commodity price crash. The results indicate that generally, companies in the resource sector tend to have conditional capital shortfall before 2000 and conditional capital surplus after 2000 owing to the boom of the commodity sector stock and the moderate-to-careful capital structure management adopted by these companies. This finding is especially valid for resource firms from developed countries, whose observations dominate the dataset used in this study. Furthermore, the analysis using the panel vector autoregressive model indicates a positive influence of commodity price, geopolitical, and economic policy uncertainties on the conditional capital shortfall. These uncertainties have also been proven to increase the conditional failure probability of firms in the sample. Lastly, the performance analysis shows that potential capital shortfall is positively related to market return, reflecting a high-risk high-return trade-off for this sector. |
| Keywords: | systematic risk index — commodity prices — macroeconomic uncertainties — panel vector autoregression |
| JEL: | E32 G32 |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:lpe:wpaper:202165&r= |
| By: | Hea-Jung Hyun (College of International Studies, Kyung Hee University, Korea); Jung Hur (Department of Economics, Sogang University, Korea) |
| Abstract: | We examine the role of export credit insurance (ECI) in Korea during two periods of financial crisis by focusing on insured exporting firms' response on the scope of exported products and destination countries. Using unique Korean firm-level data over 1995–2010, our empirical analyses show that during financial crises (e.g., the 1998 Asian financial crisis and the 2008 global financial crisis), multiproduct firms reduced the scope of their export products and the number of destination countries. However, firms with above-median levels of ECI reduced the scope of product and country significantly less than firms with below-median ECI. Core products were less likely to be dropped during the two crisis periods. After the 2008 global financial crisis, countries with high political risk and a low level of financial development were less likely to be dropped from the export market portfolios of firms with high ECI. These findings may imply that larger ECI may be related to higher risk-taking behavior of exporters under asymmetric information. |
| Keywords: | Product Scope, Country Diversification, Export Credit Insurance, Global Financial Crisis |
| JEL: | F13 F34 D22 |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:sgo:wpaper:2106&r= |
| By: | Tosapol Apaitan; Pym Manopimoke; Nuwat Nookhwun; Jettawat Pattararangrong |
| Abstract: | We use transaction-level customs data and show that there is significant heterogeneity in exchange rate pass-through (ERPT) to import prices at the Thai border. Our findings uncover significant variations in ERPT across time as well as across disaggregated sectors. By studying several structural determinants of ERPT, we find that (i) prices of homogenous goods are more sensitive to exchange rate changes compared to differentiated goods; (ii) firms with a higher degree of market power face lower ERPT; and (iii) ERPT crucially hinges upon the currency of invoice in the trade transaction. For goods invoiced in a foreign currency, the effect of ERPT is significantly higher than those priced in Thai baht. We also find that for the large majority of Thai imports that are invoiced in the US dollar under the dominant currency pricing (DCP) paradigm, price responses to the US dollar are much higher than those associated with the bilateral exchange rate vis-Ã -vis the exporters' currency, but only in the short run. In the medium run, both exchange rates become equally relevant. Finally, by investigating state-dependent properties of ERPT, we find that while Thai import prices are equally sensitive to small versus large exchange rate changes, the degree of pass-through is stronger during episodes of depreciations rather than appreciations, particularly for goods that practice DCP. |
| Keywords: | Invoice Currency; Exchange Rate Pass-through; Directional Asymmetry; Differentiated Products; Firm Market Power; Local Currency Pricing; Producer Currency Pricing; Dominant Currency Pricing |
| JEL: | E31 F14 F31 L11 |
| Date: | 2021–11 |
| URL: | http://d.repec.org/n?u=RePEc:pui:dpaper:167&r= |
| By: | Bairagi, Subir; Zereyesus, Yacob |
| Keywords: | Agribusiness, Consumer/Household Economics |
| Date: | 2021–08 |
| URL: | http://d.repec.org/n?u=RePEc:ags:iaae21:315372&r= |
| By: | Albert J. Menkveld (Vrije Universiteit Amsterdam); Anna Dreber (Stockholm School of Economics); Felix Holzmeister (University of Innsbruck); Juergen Huber (University of Innsbruck); Magnus Johannesson (Stockholm School of Economics); Michael Kirchler (University of Innsbruck); Sebastian Neusüss; Michael Razen (University of Innsbruck); Utz Weitzel (Vrije Universiteit Amsterdam); David Abad-Díaz (University of Alicante); Menachem Abudy (Bar-Ilan University); Tobias Adrian (International Monetary Fund); Yacine Ait-Sahalia (Princeton University); Olivier Akmansoy (CNRS); Jamie T. Alcock (University of Oxford); Vitali Alexeev (University of Technology Sydney); Arash Aloosh (Neoma Business School); Livia Amato (University of Chicago Booth School of Business); Diego Amaya (Wilfrid Laurier University); James J. Angel (Georgetown University); Alejandro T. Avetikian (Pontificia Universidad Católica de Chile); Amadeus Bach (University of Mannheim); Edwin Baidoo (Tennessee Technological University); Gaetan Bakalli (Auburn University); Li Bao (Toulouse 1 Capitole University); Andrea Barbon (University of St. Gallen); Oksana Bashchenko (SFI at University of Lausanne); Parampreet C. Bindra (University of Innsbruck); Geir H. Bjønnes (BI Norwegian Business School); Jeffrey R. Black (University of Memphis); Bernard S. Black (Northwestern University); Dimitar Bogoev (EDF Energy London); Santiago Bohorquez Correa (Universidad EAFIT); Oleg Bondarenko (University of Illinois at Chicago); Charles S. Bos (Vrije Universiteit Amsterdam); Ciril Bosch-Rosa (Technische Universität Berlin); Elie Bouri (Lebanese American University); Christian Brownlees (Universitat Pompeu Fabra); Anna Calamia (TBS Education); Viet Nga Cao (Monash University); Gunther Capelle-Blancard (University Paris 1 Pantheon-Sorbonne); Laura M. Capera Romero (Vrije Universiteit Amsterdam); Massimiliano Caporin (University of Padova); Allen Carrion (University of Memphis); Tolga Caskurlu (University of Amsterdam); Bidisha Chakrabarty (Saint Louis University); Jian Chen (Queen's University); Mikhail Chernov (UCLA); William Cheung (Waseda University); Ludwig B. Chincarini (University of San Francisco); Tarun Chordia (Emory University); Sheung Chi Chow (Australian National University); Benjamin Clapham (Goethe University Frankfurt); Jean-Edouard Colliard (HEC Paris); Carole Comerton-Forde (University of Melbourne); Edward Curran (Macquarie University); Thong Dao (Nottingham Trent University); Wale Dare (HEC Liège - University of Liège); Ryan J. Davies (Babson College); Riccardo De Blasis (LUM University); Gianluca F. De Nard (University of Zurich); Fany Declerck (Toulouse 1 Capitole University); Oleg Deev (Masaryk University); Hans Degryse (KU Leuven); Solomon Y. Deku (Nottingham Trent University); Christophe Desagre (UCLouvain); Mathijs A. van Dijk (Erasmus University Rotterdam); Chukwuma Dim (Frankfurt School of Finance and Management); Thomas Dimpfl (University of Hohenheim); Yun Jiang Dong (Queen's University); Philip A. Drummond (Monash University); Tom Dudda (Technische Universität Dresden); Teodor Duevski (HEC Paris); Ariadna Dumitrescu (ESADE Business School, Univ. Ramon Llull); Teodor Dyakov (EDHEC Business School); Anne Haubo Dyhrberg (University of Sydney); MichaÅ‚ DzieliÅ„ski (Stockholm University); Asli Eksi (Salisbury University); Izidin El Kalak (Cardiff University); Saskia ter Ellen (Central Bank of Norway); Nicolas Eugster (University of Queensland); Martin D. D. Evans (Georgetown University); Michael Farrell (University of Virginia); Ester Felez-Vinas (University of Technology Sydney); Gerardo Ferrara (Bank of England); El Mehdi Ferrouhi (Ibn Tofail University); Andrea Flori (Politecnico di Milano); Jonathan T. Fluharty (West Virginia University); Sean D. V. Foley (Macquarie University); Kingsley Y. L. Fong (University of New South Wales); Thierry Foucault (HEC Paris); Tatiana Franus (Bayes Business School); Francesco Franzoni (Università della Svizzera italiana); Bart Frijns (Open Universiteit); Michael Frömmel (Ghent University); Servanna M. Fu (University of Essex); Sascha C. Füllbrunn (Radboud University); Baoqing Gan (University of Technology Sydney); Ge Gao (University of Birmingham); Thomas P. Gehrig (University of Vienna); Roland Gemayel (King's College London); Dirk Gerritsen (Utrecht University); Javier Gil-Bazo (Universitat Pompeu Fabra); Dudley Gilder (Cardiff University); Lawrence R. Glosten (Columbia University); Thomas Gomez (Utrecht University); Arseny Gorbenko (Monash University); Joachim Grammig (University of Tübingen); Vincent Grégoire (HEC Montréal); Ufuk Güçbilmez (University of Glasgow); Björn Hagströmer (Stockholm University); Julien Hambuckers (HEC Liège - University of Liège); Erik Hapnes; Jeffrey H. Harris (American University); Lawrence Harris (University of Southern California); Simon Hartmann (Vienna University of Economics and Business); Jean-Baptiste Hasse (Aix-Marseille University); Nikolaus Hautsch (University of Vienna); Xue-Zhong (Tony) He (Xi'an Jiaotong-Liverpool University); Davidson Heath (University of Utah); Simon Hediger (University of Zurich); Terrence Hendershott (UC Berkeley); Ann Marie Hibbert (West Virginia University); Erik Hjalmarsson (University of Gothenburg); Seth Hoelscher (Missouri State University); Peter Hoffmann (European Central Bank); Craig W. Holden (Indiana University); Alex R. Horenstein (University of Miami); Wenqian Huang (Bank for International Settlements); Da Huang (University of Utah); Christophe Hurlin (University of Orléans); Konrad Ilczuk; Alexey Ivashchenko (Vrije Universiteit Amsterdam); Subramanian R. Iyer (University of New Mexico); Hossein Jahanshahloo (Cardiff University); Naji P. Jalkh (Saint Joseph University); Charles M. Jones (Columbia Business School); Simon Jurkatis (Bank of England); Petri Jylhä (Aalto University); Andreas T. Kaeck (University of Sussex); Gabriel Kaiser (University of Luxembourg); Arzé Karam (Durham University); Egle Karmaziene (Vrije Universiteit Amsterdam); Bernhard Kassner (University of Munich (LMU)); Markku Kaustia (Aalto University); Ekaterina Kazak (University of Manchester); Fearghal Kearney (Queen's University Belfast); Vincent van Kervel (Pontificial University of Chile); Saad A. Khan (HEC Montréal); Marta K. Khomyn (University of Technology Sydney); Tony Klein (Queen's University Belfast); Olga Klein (University of Warwick); Alexander Klos (Kiel University); Michael Koetter (Halle Institute for Economic Research); Aleksey Kolokolov (University of Manchester); Robert A. Korajczyk (Northwestern University); Roman Kozhan (University of Warwick); Jan P. Krahnen (Goethe University Frankfurt); Paul Kuhle (Universidad Autónoma de Madrid); Amy Kwan (University of Sydney); Quentin Lajaunie (Paris Dauphine University); F. Y. Eric C. Lam (Hong Kong Institute for Monetary and Financial Research); Marie Lambert (HEC Liège - University of Liège); Hugues Langlois (HEC Paris); Jens Lausen (Goethe University Frankfurt); Tobias Lauter (Leibniz University Hannover); Markus Leippold (University of Zurich); Vladimir Levin (University of Luxembourg); Yijie Li (SandP Global Ratings); Hui Li (La Trobe University); Chee Yoong Liew (UCSI University); Thomas Lindner (WU Vienna University of Economics and Business); Oliver Linton (University of Cambridge); Jiacheng Liu (Purdue University); Anqi Liu (University of Sydney); Guillermo Llorente (Universidad Autónoma de Madrid); Matthijs Lof (Aalto University); Ariel Lohr (Arizona State University); Francis Longstaff (UCLA); Alejandro Lopez-Lira (University of Florida); Shawn Mankad (Cornell University); Nicola Mano (SFI at USI Lugano); Alexis Marchal (EPFL); Charles Martineau (University of Toronto); Francesco Mazzola (Erasmus University Rotterdam); Debrah Meloso (TBS Education); Michael G. Mi (University of Sydney); Roxana Mihet (SFI at HEC Lausanne); Vijay Mohan (RMIT University); Sophie Moinas (Toulouse 1 Capitole University); David Moore (Loyola Marymount University); Liangyi Mu (The University of Manchester); Dmitriy Muravyev (Michigan State University); Dermot Murphy (University of Illinois at Chicago); Gabor Neszveda (John von Neumann University); Christian Neumeier (Justus-Liebig University); Ulf Nielsson (Copenhagen Business School); Mahendrarajah Nimalendran (University of Florida); Sven Nolte (Radboud University); Lars L. Norden (Stockholm University); Peter W. O'Neill (Financial Conduct Authority); Khaled Obaid (California State University - East Bay); Bernt A. Ødegaard (University of Stavanger); Per Östberg (University of Zurich); Emiliano Pagnotta (Singapore Management University); Marcus Painter (Saint Louis University); Stefan Palan (University of Graz); Imon J. Palit (RMIT University); Andreas Park (University of Toronto Mississauga); Roberto Pascual (University of the Balearic Islands); Paolo Pasquariello (University of Michigan); Lubos Pastor (University of Chicago Booth School of Business); Vinay Patel (University of Technology Sydney); Andrew J. Patton (Duke University); Neil D. Pearson (University of Illinois at Urbana-Champaign); Loriana Pelizzon (Goethe University Frankfurt); Michele Pelli (SFI at University of Zurich); Matthias Pelster (Paderborn University); Christophe Pérignon (HEC Paris); Cameron Pfiffer (University of Oregon); Richard Philip (University of Sydney); Tomáš Plíhal (Masaryk University); Puneet Prakash (Missouri State University); Oliver-Alexander Press (Copenhagen Business School); Tina Prodromou (University of Wollongong); Marcel Prokopczuk (Leibniz University Hannover); Talis Putnins (University of Technology Sydney); Ya Qian; Gaurav Raizada (IIM Ahmedabad); David Rakowski (University of Texas at Arlington); Angelo Ranaldo (University of St. Gallen); Luca Regis (University of Torino); Stefan Reitz (Kiel university); Thomas Renault (Université Paris 1 Panthéon-Sorbonne); Rex W. Renjie (Vrije Universiteit Amsterdam); Roberto Reno (University of Verona); Steven J. Riddiough (University of Toronto); Kalle Rinne (University of Luxembourg); Paul J. Rintamäki (Aalto University); Ryan Riordan (Queen's University); Thomas Rittmannsberger (University of Innsbruck); Iñaki Rodríguez Longarela (Stockholm University); Dominik Roesch (State University of New York at Buffalo); Lavinia Rognone (University of Manchester); Brian Roseman (Oklahoma State University); Ioanid Rosu (HEC Paris); Saurabh Roy (University of Massachusetts, Amherst); Nicolas Rudolf (University of Lausanne); Stephen R. Rush (Bowling Green State University); Khaladdin Rzayev (University of Edinburgh); Aleksandra A. Rzeźnik (York University); Anthony Sanford (University of Maryland); Harikumar Sankaran (New Mexico state University); Asani Sarkar (Federal Reserve Bank of New York); Lucio Sarno (University of Cambridge); Olivier Scaillet (SFI at University of Geneva); Stefan Scharnowski (University of Mannheim); Klaus R. Schenk-Hoppé (University of Manchester); Andrea Schertler (University of Graz); Michael Schneider (Deutsche Bundesbank); Florian Schroeder (Macquarie University); Norman Schürhoff (SFI at University of Lausanne); Philipp Schuster (University of Stuttgart); Marco A. Schwarz (Düsseldorf Institute for Competition Economics); Mark S. Seasholes (Arizona State University); Norman J. Seeger (Vrije Universiteit Amsterdam); Or Shachar (Federal Reserve Bank of New York); Andriy Shkilko (Wilfrid Laurier University); Jessica Shui (Federal Housing Finance Agency); Mario Sikic (University of Zurich); Giorgia Simion (WU Vienna University of Economics and Business); Lee A. Smales (University of Western Australia); Paul Söderlind (University of St. Gallen); Elvira Sojli (University of New South Wales); Konstantin Sokolov (University of Memphis); Jantje Sönksen (University of Tübingen); Laima Spokeviciute (Cardiff University); Denitsa Stefanova (University of Luxembourg); Marti G. Subrahmanyam (NYU Stern); Barnabas Szaszi (ELTE, Eotvos Lorand University); Oleksandr Talavera (University of Birmingham); Yuehua Tang (University of Florida); Nick Taylor (University of Bristol); Wing Wah Tham (University of New South Wales); Erik Theissen (University of Mannheim); Julian Thimme (Karlsruhe Institute of Technology); Ian Tonks (University of Bristol); Hai Tran (Loyola Marymount University); Luca Trapin (University of Bologna); Anders B. Trolle (Copenhagen Business School); M. Andreea Vaduva (Universidad Carlos III de Madrid); Giorgio Valente (Hong Kong Monetary Authority); Robert A. Van Ness (University of Mississippi); Aurelio Vasquez (ITAM); Thanos Verousis (University of Essex); Patrick Verwijmeren (Erasmus University Rotterdam); Anders Vilhelmsson (Lund University); Grigory Vilkov (Frankfurt School of Finance and Management); Vladimir Vladimirov (University of Amsterdam); Sebastian Vogel (Erasmus University Rotterdam); Stefan Voigt (University of København); Wolf Wagner (Erasmus University Rotterdam); Thomas Walther (Utrecht University); Patrick Weiss (Vienna Graduate School of Finance); Michel van der Wel (Erasmus University Rotterdam); Ingrid M. Werner (The Ohio State University); Joakim Westerholm (University of Sydney); Christian Westheide (University of Vienna); Hans C. Wika (Norges Bank); Evert Wipplinger (Vrije Universiteit Amsterdam); Michael Wolf (University of Zurich); Christian C. P. Wolff (University of Luxembourg); Leonard Wolk (Vrije Universiteit Amsterdam); Wing-Keung Wong (Asia University); Jan Wrampelmeyer (Vrije Universiteit Amsterdam); Zhen-Xing Wu (Zhongnan University of Economics and Law); Shuo Xia (Halle Institute for Economic Research); Dacheng Xiu (University of Chicago Booth School of Business); Ke Xu (University of Victoria); Caihong Xu (Stockholm University); Pradeep K. Yadav (University of Oklahoma); José Yagüe (University of Murcia); Cheng Yan (University of Essex); Antti Yang (Erasmus University Rotterdam); Woongsun Yoo (Central Michigan University); Wenjia Yu (Aalto University); Yihe Yu (University at Buffalo); Shihao Yu (Vrije Universiteit Amsterdam); Bart Z. Yueshen (INSEAD); Darya Yuferova (Norwegian School of Economics (NHH)); Marcin Zamojski (University of Gothenburg); Abalfazl Zareei (Stockholm University); Stefan M. Zeisberger (Radboud University); Lu Zhang (University of Luxembourg); S. Sarah Zhang (University of Manchester); Xiaoyu Zhang (Vrije Universiteit Amsterdam); Lu Zhao (Southwestern University of Finance and Economics); Zhuo Zhong (University of Melbourne); Zeyang (Ivy) Zhou (University of Wollongong); Chen Zhou (Erasmus University Rotterdam); Xingyu S. Zhu (Stockholm School of Economics); Marius Zoican (University of Toronto Mississauga); Remco Zwinkels (Vrije Universiteit Amsterdam) |
| Abstract: | In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants. |
| Date: | 2021–11–23 |
| URL: | http://d.repec.org/n?u=RePEc:grz:wpsses:2021-08&r= |
| By: | Powdthavee, Nattavudh (University of Warwick); Riyanto, Yohanes E. (Nanyang Technological University, Singapore); Wong, Erwin (Nanyang Technological University, Singapore); Yeo, Jonathan (Nanyang Technological University, Singapore); Chan, Qi Yu (Nanyang Technological University, Singapore) |
| Abstract: | With the COVID-19 pandemic still raging and the vaccination program still rolling out, there continues to be an immediate need for public health officials to better understand the mechanisms behind the deep and perpetual divide over face masks in America. Using a random sample of Americans (N=615), following a pre-registered experimental design and analysis plan, we first demonstrated that mask wearers were not innately more cooperative as individuals than non-mask wearers in the Prisoners' Dilemma (PD) game when information about their own and the other person's mask usage was not salient. However, we found strong evidence of in-group favouritism among both mask and non-mask wearers when information about the other partner's mask usage was known. Non-mask wearers were 23 percentage points less likely to cooperate than mask wearers when facing a mask-wearing partner, and 26 percentage points more likely to cooperate than mask wearers when facing a non-mask-wearing partner. Our analysis suggests social identity effects as the primary reason behind people's decision whether to wear face masks during the pandemic. |
| Keywords: | face mask, COVID-19, cooperation, social identity, prisoners' dilemma |
| JEL: | C9 I1 |
| Date: | 2021–09 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp14715&r= |